1 Section 1

## bmp db
bmpDF <- read.csv("c:/users/95218.CHARLOTTE/Documents/R/Pilot-SCM-App/bWQ BMP FlatFile BMP Indiv Anal_Rev 10-2014.csv",
                   stringsAsFactors=FALSE, sep=",", header=TRUE)

        ## IBMPDB Boxplots

pBox <- plot_ly(type = 'box') %>%
    add_boxplot(y=bmpDF[which(bmpDF$Monitoring.Station.Type=="Inflow"),
                        "WQ.Analysis.Value"],
                boxpoints = FALSE,
                marker = list(color = 'rgb(7,40,89)'),
                line = list(color = 'rgb(7,40,89)'),
                name = "Influent") %>%
    add_boxplot(y = bmpDF[which(bmpDF$Monitoring.Station.Type=="Outflow"),
                          "WQ.Analysis.Value"],
                name = "Effluent",
                boxpoints = FALSE,
                marker = list(color = 'rgb(9,56,125)'),
                line = list(color = 'rgb(9,56,125)'))
pBox

        ## Simple table
        ## output$boxTable0 <- renderTable({
        ##     temp <- ibmpDataset()
        ##     inf <- temp[which(temp$Monitoring.Station.Type=="Inflow"),]
        ##     eff <- temp[which(temp$Monitoring.Station.Type=="Outflow"),]

        ##     tt <- data.frame(
        ##         Inflow=c(nrow(inf), median(inf$WQ.Analysis.Value),
        ##                  mean(inf$WQ.Analysis.Value), min(inf$WQ.Analysis.Value),
        ##                  max(inf$WQ.Analysis.Value)),
        ##         Outflow=c(nrow(eff), median(eff$WQ.Analysis.Value),
        ##                   mean(eff$WQ.Analysis.Value), min(eff$WQ.Analysis.Value),
        ##                   max(eff$WQ.Analysis.Value)),
        ##         row.names=c("n", "Median", "Mean", "Min.", "Max."))

        ##     tt}, rownames=TRUE
        ## )

2 Section 2

3 Section 3

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